Seasonal Variations in The Moduli of Unbound
Pavement Layers

FOREWORD

The in situ moduli of unbound pavement materials vary on a
seasonal basis as a function of temperature and moisture
conditions. Knowledge of these variations is required for accurate
prediction of pavement life for pavement design and other pavement
management activities. The primary objective of this study is to
advance the rational estimation of seasonal variations in
backcalculated pavement layer moduli using data collected via the
Seasonal Monitoring Program of the Long-Term Pavement Performance
(LTPP) Program. Principal components of this endeavor included:
evaluation of the moisture predictive capabilities of the Enhanced
Integrated Climatic Model (EICM); development of empirical models
to predict backcalculated pavement layer moduli as a function of
moisture content, stress state, and other explanatory variables;
and trial application of the models developed to prediction
backcalculated moduli for unbound pavement layers.

This investigation yielded two key findings. First, it provided
the impetus for developing EICM Version 2.6 by demonstrating the
practical inadequacies of EICM Versions 2.0 and 2.1 when applied to
the prediction of in situ moisture content, and then demonstrated
that improvement in the moisture predictive capability of the EICM
had been achieved in Version 2.6. Second, the research identified
fundamental discrepancies between layer moduli backcalculated using
linear layered-elastic theory and the laboratory resilient modulus
test conditions.

Gary L. Henderson
Director, Office of Infrastructure
Research and Development

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The in situ moduli of unbound pavement materials vary on a
seasonal basis as a function of temperature and moisture
conditions. Knowledge of these variations is required for accurate
prediction of pavement life for pavement design and other pavement
management activities. The primary objective of this study is to
advance the rational estimation of seasonal variations in
backcalculated pavement layer moduli using data collected via the
Seasonal Monitoring Program of the Long-Term Pavement Performance
Program. Principal components of this endeavor included: evaluation
of the moisture predictive capabilities of the Enhanced Integrated
Climatic Model (EICM); development of empirical models to predict
backcalculated pavement layer moduli as a function of moisture
content, stress state, and other explanatory variables; and trial
application of the models developed to prediction backcalculated
moduli for unbound pavement layers.

This investigation yielded two key findings. First, it provided
the impetus for developing EICM Version 2.6 by demonstrating the
practical inadequacies of EICM Versions 2.0 and 2.1 when applied to
the prediction of in situ moisture content, and then demonstrated
that substantial improvement in the moisture predictive capability
of the EICM had been achieved in Version 2.6. Second, the research
identified fundamental discrepancies between layer moduli
backcalculated using linear-layered elastic theory and the
laboratory resilient modulus test conditions.

Other important findings included (1) variation in moisture
content is not always the most important factor associated with
seasonal variations in pavement layer moduli, and (2) a model form
that fits linear elastic backcalculated moduli reasonably well. The
overall accuracy of the modulus predictions achieved in the trial
application of the predictive models was not fully acceptable.
Several avenues for further research to improve upon these results
are identified.